An Optimization Study of Occupant Restraint System for Different BMI Senior Women Protection in Frontal Impacts

With the rapid development of car crash sensing and identification technology, the application of pre-triggering airbag system is becoming an important option to improve vehicle safety. Thus, the present study aims to investigate the injury protection ability of pre-triggering airbag system and optimize its performance in frontal crashes regarding the key physical parameters. A driver restraint system model established and validated by National Crash Analysis Center was employed and validated for studying the injury protection ability of pre-triggering airbag system. Then, the influences of airbag triggering time, airbag volume scaling factor, inflator mass flow, and exhaust orifice size of pre-triggering airbag system on driver’s head and chest injuries were analyzed. Finally, the weighted injury criterion was selected as the evaluation index to optimize the pre-triggering airbag system. The results show the pre-triggering airbag should be designed with a larger airbag volume and inflator mass flow rate and smaller exhaust orifice. The optimized restraint system design presents a reduction of weighted injury criterion values in 100% and 40% overlapped frontal impacts reaching 25.63% and 42.23%, respectively.

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Research on the Safety of Rear Seat Occupants in the Frontal Collision

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.569.795 ◽

2012 ◽

Vol 569 ◽

pp. 795-799

Author(s):

Liang Hong ◽

Yun Teng Wu

Keyword(s):

Simulation Model ◽

Rear Seat ◽

Performance Criterion ◽

Restraint System ◽

Vehicle Model ◽

Occupant Restraint System ◽

Head Injury Criterion ◽

Frontal Collision ◽

Seat Cushion ◽

Left And Right

To study the injury values rear seat occupants sustain in the frontal collision, this paper constructed the simulation model of the rear occupant restraint system of a vehicle model using MADYMO software. The influence of the rear 3-point seatbelt stiffness and retractor locking feature, the rear seat cushion stiffness and angle with the vehicle floor on head injury criterion HIC36, thorax 3ms resultant acceleration T3MS, thorax performance criterion THPC, left and right femur force of rear occupants were analysed through the simulation model. The conclusion shows that HIC36 drops when the seatbelt stiffness increases and retractor locking feature decreases compared to the original values; HIC36, T3MS, left and right femur force become less when the seat cushion stiffness decreases and angle increases compared to the original values.

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Stochastic Kriging for Crashworthiness Optimization Accounting for Simulation Noise

Volume 11B: 46th Design Automation Conference (DAC) ◽

10.1115/detc2020-22532 ◽

2020 ◽

Author(s):

Seyed Saeed Ahmadisoleymani ◽

Samy Missoum

Keyword(s):

Stochastic Process ◽

Optimization Algorithm ◽

Stationary Stochastic Process ◽

Expected Improvement ◽

Restraint System ◽

Stochastic Kriging ◽

Occupant Restraint System ◽

Crashworthiness Optimization ◽

Surrogate Based Optimization ◽

Available Information

Abstract Vehicle crash simulations are notoriously costly and noisy. When performing crashworthiness optimization, it is therefore important to include available information to quantify the noise in the optimization. For this purpose, a stochastic kriging can be used to account for the uncertainty due to the simulation noise. It is done through the addition of a non-stationary stochastic process to the deterministic kriging formulation. This stochastic kriging, which can also be used to include the effect of random non-controllable parameters, can then be used for surrogate-based optimization. In this work, a stochastic kriging-based optimization algorithm is proposed with an infill criterion referred to as the Augmented Expected Improvement, which, unlike its deterministic counterpart the Expect Improvement, accounts for the presence of irreducible aleatory variance due to noise. One of the key novelty of the proposed algorithm stems from the approximation of the aleatory variance and its update during the optimization. The proposed approach is applied to the optimization of two problems including an analytical function and a crashwor-thiness problem where the components of an occupant restraint system of a vehicle are optimized.

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Development of Occupant Restraint System for SUV - Telco Experience

10.4271/2003-26-0027 ◽

2003 ◽

Author(s):

S. Ravishankar ◽

C. Anil Kumar ◽

B. S. Praveen

Keyword(s):

Restraint System ◽

Occupant Restraint System

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Study on the Difference of Frontal Impact Response among People of Different Sizes

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.34-35.111 ◽

2010 ◽

Vol 34-35 ◽

pp. 111-116 ◽

Cited By ~ 1

Author(s):

Li Bo Cao ◽

Chong Zhen Cui ◽

Ning Yu Zhu ◽

Huan Chen

Keyword(s):

Human Body ◽

Injury Risk ◽

Simulation Models ◽

Restraint System ◽

Frontal Impact ◽

Occupant Restraint System ◽

Impact Simulation ◽

The Difference ◽

Human Body Models ◽

Multi Body

In this article, seven frontal impact simulation models with same restraint system and different human body models were established through the use of multi-body kinematics software MADYMO. The injuries in head, chest and femurs of different human models and the differences of these injuries were analyzed in detail. The weighted injury criterion was adopted to evaluate the overall injuries of different human body models. The results shows that the injury risk of smaller human body is much higher than the taller human body, and existing occupant restraint system that protects the 50th percentile American occupant well protects other size occupant poorly.

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